Description: 本代码是用java语言编写的基于决策树c4.5算法的数据挖掘程序，它可以在很多领域如股票系统中使用 -the code is written in java-based Decision Tree Algorithm Bank data mining process, it can in many areas such as the use of the stock system Platform: |
Size: 231424 |
Author:飞翔 |
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Description: 用c++实现的决策树算法，windows环境下，希望对学习数据结构和算法的朋友有所帮助。-achieve with the Decision Tree Algorithm, windows environment, and I hope to learn from data structures and algorithms friends help. Platform: |
Size: 149504 |
Author:yu |
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Description: 数据挖掘中的决策树C4.5算法的实现,用matlab实现-Data Mining Decision Tree Algorithm of C4.5, using Matlab to achieve Platform: |
Size: 2048 |
Author:利军 |
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Description: 这是决策树C4.5算法的java版源码。希望大家能喜欢，愿共同分享！-Decision Tree Algorithm C4.5 java version of the source code. Hope you will like it is willing to share! Platform: |
Size: 1024 |
Author:gosiger |
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Description: One kind of decision-making tree algorithm, can be seen as one kind data mining algorithm ,find the rule from large-scale data middle. Platform: |
Size: 15360 |
Author:渐令 |
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Description: this decision tree ID3 algorithm, this algorithm is one of decision tree algorithm like cart, chaid, c4.5, etc-this is decision tree ID3 algorithm, this algorithm is one of decision tree algorithm like cart, chaid, c4.5, etc Platform: |
Size: 465920 |
Author:sang |
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Description: 决策树算法的matlab实现，主要适用的是id3
算法思想-Decision Tree Algorithm to achieve the matlab main id3 algorithm is applicable to thinking Platform: |
Size: 6144 |
Author:fj |
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Description: Recently, information security has become a key issue
in information technology as the number of computer security
breaches are exposed to an increasing number of security threats. A
variety of intrusion detection systems (IDS) have been employed for
protecting computers and networks from malicious network-based or
host-based attacks by using traditional statistical methods to new data
mining approaches in last decades. However, today s commercially
available intrusion detection systems are signature-based that are not
capable of detecting unknown attacks. In this paper, we present a
new learning algorithm for anomaly based network intrusion
detection system using decision tree algorithm that distinguishes
attacks from normal behaviors and identifies different types of
intrusions. Experimental results on the KDD99 benchmark network
intrusion detection dataset demonstrate that the proposed learning
algorithm achieved 98 detection rate (DR) in comparison with
other existing methods.-Recently, information security has become a key issue
in information technology as the number of computer security
breaches are exposed to an increasing number of security threats. A
variety of intrusion detection systems (IDS) have been employed for
protecting computers and networks from malicious network-based or
host-based attacks by using traditional statistical methods to new data
mining approaches in last decades. However, today s commercially
available intrusion detection systems are signature-based that are not
capable of detecting unknown attacks. In this paper, we present a
new learning algorithm for anomaly based network intrusion
detection system using decision tree algorithm that distinguishes
attacks from normal behaviors and identifies different types of
intrusions. Experimental results on the KDD99 benchmark network
intrusion detection dataset demonstrate that the proposed learning
algorithm achieved 98 detection rate (DR) in comparison with
other existing methods. Platform: |
Size: 312320 |
Author:keerthi |
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Description: 一个决策树算法的ppt，里面详细的介绍了决策树算法-A decision tree algorithm ppt, which describes in detail the decision tree algorithm Platform: |
Size: 385024 |
Author:杨啸晗 |
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Search - decision tree algorithm